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<li><a class="reference internal" href="#">PCA example with Iris Data-set</a></li>
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<section class="sphx-glr-example-title" id="pca-example-with-iris-data-set">
<span id="sphx-glr-auto-examples-decomposition-plot-pca-iris-py"></span><h1>PCA example with Iris Data-set<a class="headerlink" href="#pca-example-with-iris-data-set" title="Link to this heading">¶</a></h1>
<p>Principal Component Analysis applied to the Iris dataset.</p>
<p>See <a class="reference external" href="https://en.wikipedia.org/wiki/Iris_flower_data_set">here</a> for more
information on this dataset.</p>
<img src="../../_images/sphx_glr_plot_pca_iris_001.png" srcset="../../_images/sphx_glr_plot_pca_iris_001.png" alt="plot pca iris" class = "sphx-glr-single-img"/><div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Code source: Gaël Varoquaux</span>
<span class="c1"># License: BSD 3 clause</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="c1"># unused but required import for doing 3d projections with matplotlib < 3.2</span>
<span class="kn">import</span> <span class="nn">mpl_toolkits.mplot3d</span> <span class="c1"># noqa: F401</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="kn">import</span> <span class="n">datasets</span><span class="p">,</span> <span class="n">decomposition</span>
<a href="https://numpy.org/doc/stable/reference/random/generated/numpy.random.seed.html#numpy.random.seed" title="numpy.random.seed" class="sphx-glr-backref-module-numpy-random sphx-glr-backref-type-py-function"><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span></a><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
<span class="n">iris</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.datasets.load_iris.html#sklearn.datasets.load_iris" title="sklearn.datasets.load_iris" class="sphx-glr-backref-module-sklearn-datasets sphx-glr-backref-type-py-function"><span class="n">datasets</span><span class="o">.</span><span class="n">load_iris</span></a><span class="p">()</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">iris</span><span class="o">.</span><span class="n">data</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">iris</span><span class="o">.</span><span class="n">target</span>
<span class="n">fig</span> <span class="o">=</span> <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.figure.html#matplotlib.pyplot.figure" title="matplotlib.pyplot.figure" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">figure</span></a><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.clf.html#matplotlib.pyplot.clf" title="matplotlib.pyplot.clf" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">clf</span></a><span class="p">()</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">,</span> <span class="n">projection</span><span class="o">=</span><span class="s2">"3d"</span><span class="p">,</span> <span class="n">elev</span><span class="o">=</span><span class="mi">48</span><span class="p">,</span> <span class="n">azim</span><span class="o">=</span><span class="mi">134</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_position</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">0.95</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.cla.html#matplotlib.pyplot.cla" title="matplotlib.pyplot.cla" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">cla</span></a><span class="p">()</span>
<span class="n">pca</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="sklearn.decomposition.PCA" class="sphx-glr-backref-module-sklearn-decomposition sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">decomposition</span><span class="o">.</span><span class="n">PCA</span></a><span class="p">(</span><span class="n">n_components</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">pca</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">pca</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">label</span> <span class="ow">in</span> <span class="p">[(</span><span class="s2">"Setosa"</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="p">(</span><span class="s2">"Versicolour"</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="p">(</span><span class="s2">"Virginica"</span><span class="p">,</span> <span class="mi">2</span><span class="p">)]:</span>
<span class="n">ax</span><span class="o">.</span><span class="n">text3D</span><span class="p">(</span>
<span class="n">X</span><span class="p">[</span><span class="n">y</span> <span class="o">==</span> <span class="n">label</span><span class="p">,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">(),</span>
<span class="n">X</span><span class="p">[</span><span class="n">y</span> <span class="o">==</span> <span class="n">label</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">+</span> <span class="mf">1.5</span><span class="p">,</span>
<span class="n">X</span><span class="p">[</span><span class="n">y</span> <span class="o">==</span> <span class="n">label</span><span class="p">,</span> <span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">(),</span>
<span class="n">name</span><span class="p">,</span>
<span class="n">horizontalalignment</span><span class="o">=</span><span class="s2">"center"</span><span class="p">,</span>
<span class="n">bbox</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">edgecolor</span><span class="o">=</span><span class="s2">"w"</span><span class="p">,</span> <span class="n">facecolor</span><span class="o">=</span><span class="s2">"w"</span><span class="p">),</span>
<span class="p">)</span>
<span class="c1"># Reorder the labels to have colors matching the cluster results</span>
<span class="n">y</span> <span class="o">=</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.choose.html#numpy.choose" title="numpy.choose" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-function"><span class="n">np</span><span class="o">.</span><span class="n">choose</span></a><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">float</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">X</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">X</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">X</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">],</span> <span class="n">c</span><span class="o">=</span><span class="n">y</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">nipy_spectral</span><span class="p">,</span> <span class="n">edgecolor</span><span class="o">=</span><span class="s2">"k"</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_ticklabels</span><span class="p">([])</span>
<span class="n">ax</span><span class="o">.</span><span class="n">yaxis</span><span class="o">.</span><span class="n">set_ticklabels</span><span class="p">([])</span>
<span class="n">ax</span><span class="o">.</span><span class="n">zaxis</span><span class="o">.</span><span class="n">set_ticklabels</span><span class="p">([])</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span>
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<p class="rubric">Related examples</p>
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<div class="sphx-glr-thumbnail-title">Sparsity Example: Fitting only features 1 and 2</div>
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<div class="sphx-glr-thumbnail-title">Comparison of LDA and PCA 2D projection of Iris dataset</div>
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